Currently, end users regularly utilize smartphones, computing devices, and other communications-based technologies to place and receive phone calls, access various types of content and services, perform a variety of functions, or a combination thereof. When an end user attempts to communicate using such devices and technologies, the end user is often located in a shared-space environment, such as, but not limited to, a park, an office, a passenger car, a train, a bus, an airport, or a mall. Such environments may include ambient noises, such as, but not limited to, noises generated from vehicles, machinery, and animals that may potentially interfere with the end user's communications. Additionally, such environments may also include interfering end users, who may be making concurrent phone calls or other communications that may interfere with the communications made by the end user. In such a scenario, each end user's voice signals will propagate through the air, reach other nearby end users, be picked up by the microphones of the nearby end users' devices, and become undesired input signals for the nearby end users. This problem typically falls in the general category known as multi-talker speech separation or blind source separation.
Currently, in order to counteract or cancel such ambient noise and interfering end users, noise cancellation algorithms and technologies have been utilized to separate a targeted end user's audio signals from the ambient noise and audio signals generated by the interfering end users. However, current noise suppression algorithms and technologies typically require predefining the locations of the sources of the ambient noise, the location of the targeted end user, and the locations of interfering end users. While the use of microphone arrays may assist in counteracting the interfering audio signals via dynamic acoustic beam steering, microphone arrays are often impractical and expensive, particularly in the context of shared-space environments. As a result, currently existing noise cancellation technologies do not provide an optimal and cost-effective solution for end users.